Impact of uncertainties on the translation of remaining pipe wall thickness to structural capacity
Bibliographic record
Abstract
Drinking water distribution systems form essential components of most urban centres. Water mains (or pipes) buried in the soil/backfill are exposed to different deleterious reactions and as a result, the design factor of safety may significantly degrade, leading to structural failure. In particular, metallic distribution and trunk mains are subject to corrosion. Proactive pipeline management, which entails timely maintenance, repair andrenovation, can increase the pipe service life. Several non-destructive evaluation (NDE) techniques have recently become available to measure the remaining wall thickness of metallic pipes. In this paper, an analytical model based on Winkler-type pipe-soil interaction (WPSI) is used to translate the remaining pipe wall thickness to current structural factor of safety. The WPSI model takes into consideration external (traffic, frost, etc) and internal (operating and surge pressures) loads, temperature changes, andloss of bedding support as well as the reduction of pipe structural capacity in the presence of corrosion pits. Uncertainties in the input data/parameters are handled using possibility theory and fuzzy arithmetic. Sensitivity analysis is carried out to identify the critical data/parameters that merit further investigation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".